ABSTRACT
The investigation of antigen-laden droplet deposition patterns on antibody-immobilized substrates has potential for disease detection. Stationary droplets that contain antigens on surfaces immobilized with antibodies can function as microreactors. Temperature modulation enhances reaction efficiency and reduces detection time in droplet-based systems. Thus, the aim of this study is to explore the impact of substrate heating on the structures of protein deposits and the influence of substrate temperature on thermo-solutal Marangoni convection within the droplets. Previous research has explored deposition patterns as diagnostic tools, but limited investigations have focused on the effects of substrate heating on protein deposit structures and the influence of substrate temperature on thermo-solutal Marangoni convection within droplets, creating a knowledge gap. In this study, we conducted experiments to explore how heating the substrate affects the deposition patterns of droplets containing prostate-specific antigen (PSA) on a substrate immobilized with anti-PSA IgG. Additionally, we investigated the thermo-solutal Marangoni convection within these droplets. Our findings reveal distinct deposition patterns classified into dendritic structures (heterogeneous), transitional patterns, and needle-like (homogeneous) structures. The presence of prominent coffee rings and the variation in crystal size across different groups highlight the interplay between thermal and solutal Marangoni advection. Entropy analysis provides insights into structural differences within and between patterns. This work optimizes substrate temperatures for reduced evaporation and detection times while preserving protein integrity, advancing diagnostic tool development, and improving understanding of droplet-based systems.
ABSTRACT
The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Community-driven and highly interdisciplinary, the project is collaborative and supports community standards, open access, and the FAIR data principles. The coordination of community work allowed for an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework links key molecules highlighted from broad omics data analysis and computational modeling to dysregulated pathways in a cell-, tissue- or patient-specific manner. We also employ text mining and AI-assisted analysis to identify potential drugs and drug targets and use topological analysis to reveal interesting structural features of the map. The proposed framework is versatile and expandable, offering a significant upgrade in the arsenal used to understand virus-host interactions and other complex pathologies.
ABSTRACT
We describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses.
ABSTRACT
The evaporation of antigen-laden sessile droplets on antibody-immobilized PDMS substrates could be used in place of microwells for detection purposes owing to the lesser requirements of analytes and a reduced reaction time. To develop such techniques, the effects of different parameters on the reaction efficiency and on the resulting deposition patterns of antigens on the surface after evaporation need to be well understood. While the resultant deposition patterns from the evaporation of droplets of biological fluids on surfaces are being studied for various biomedical applications, systems where the analyte of interest in the droplet binds to the surface have not been investigated until now. While the effect of temperature on the internal convection within sessile droplets has been studied, the effect of the analyte (antigen in this work) concentration and the analyte-surface (antigen-antibody in this work) binding on the internal convection has not been studied until now. Therefore, to gain insight, the evaporation dynamics of sessile droplets with different concentrations of antigens along with polystyrene microspheres (used as tracers) in phosphate-buffered saline (PBS) on antibody-immobilized PDMS substrates were experimentally studied using microparticle image velocimetry (PIV). It was found that Marangoni flow due to concentration gradients and surface reactions was responsible for the observed velocity field. The antibody-antigen reaction (as compared to the control case of no surface reaction) and higher concentrations of prostate specific antigen (PSA) resulted in increased strength of Marangoni convection. To obtain further insight into the different deposition patterns obtained, the contributions of different particle-particle and particle-substrate forces were determined, and it was observed that the Marangoni forces along with surface tension and DLVO forces create a uniform deposition of the particles present within the droplet. This learning could be used to design biosensors.
